The Deployment That Saved Instance History

In the middle of a sprawling coding session to build a distributed GPU proving management system for Filecoin's Curio protocol, one message stands out as a quiet but critical milestone. Message 1401 is deceptively simple — a single bash command that copies a binary to a remote server and restarts a service:

[bash] scp /tmp/czk/vast-manager 10.1.2.104:/tmp/vast-manager.new && ssh 10.1.2.104 'sudo systemctl stop vast-manager && sudo mv /tmp/vast-manager.new /usr/local/bin/vast-manager && sudo chmod +x /usr/local/bin/vast-manager && sudo systemctl start vast-manager && sleep 1 && sudo systemctl is-active vast-manager'
active

The response is a single word: "active". The service is running. But behind this routine deployment lies the resolution of a fundamental data integrity problem that threatened the entire operational visibility of the proving infrastructure.

The Context: Why This Deployment Was Necessary

To understand why this message matters, one must understand the problem it solved. The vast-manager system is a custom control plane for managing GPU proving instances rented from Vast.ai, a marketplace for distributed compute. The manager tracks instances through their lifecycle: registration, parameter download, benchmarking, and active proving. When an instance completes its work or fails, it gets "killed" — destroyed on the Vast platform.

The problem was that killing an instance also erased all knowledge of it. The Vast.ai API no longer returned data for destroyed instances, and the manager had no fallback. Once an instance was killed, its GPU type, location, SSH command, cost, and — most critically — its benchmark performance data all vanished from the dashboard. Logs persisted only in an in-memory ring buffer that survived until the manager process restarted. The retention window for killed instances was a mere 24 hours, after which even the database row was purged.

This was more than an inconvenience. The entire system was designed around a data-driven approach to hardware discovery: benchmark results were stored in a host_perf table keyed by machine_id, and the offers panel used this data to overlay known performance on available instances. If a killed instance's metadata disappeared, there was no way to connect its benchmark results back to a specific machine. The system could not learn from its own history.

The assistant's solution was comprehensive. First, it added twelve new columns to the SQLite instances table to store vast-sourced metadata: vast_id, host_id, machine_id, gpu_name, num_gpus, dph_total, geolocation, cpu_name, cpu_ram_mb, gpu_ram_mb, ssh_cmd, public_ip, and status_msg. Because SQLite's CREATE TABLE IF NOT EXISTS does not alter existing tables, the assistant wrote a migration block using ALTER TABLE statements, wrapped in error handling to gracefully skip columns that already existed. Second, it added a new step in the monitor cycle — the periodic loop that reconciles database state with the Vast API — to persist this metadata whenever a registered instance matched a live Vast instance. Third, it updated the dashboard handler to fall back to database-stored metadata when the Vast cache had no entry for an instance, ensuring killed instances still displayed their GPU, location, and other details. Fourth, it extended the cleanup retention from 24 hours to 7 days, giving operators a full week to review historical instance data.

All of these changes were made across multiple edits to /tmp/czk/cmd/vast-manager/main.go. The previous message (msg 1400) had compiled the binary successfully, producing the file /tmp/czk/vast-manager. Message 1401 is the deployment of that compiled artifact.

The Deployment Command: Anatomy of a Production Push

The command in message 1401 follows a pattern used throughout the session, refined through repeated practice. It is a study in disciplined operational procedure:

  1. scp /tmp/czk/vast-manager 10.1.2.104:/tmp/vast-manager.new — The binary is copied to the remote controller host under a .new suffix, avoiding overwriting the running binary in-place. This is a safe staging pattern: if the copy fails, the existing binary remains untouched.
  2. sudo systemctl stop vast-manager — The service is stopped cleanly via systemd. This ensures the old binary is no longer executing before we replace it.
  3. sudo mv /tmp/vast-manager.new /usr/local/bin/vast-manager — The new binary is moved into the final location, atomically replacing the old one. The .new suffix is dropped.
  4. sudo chmod +x /usr/local/bin/vast-manager — Execute permissions are set (belt-and-suspenders, since the original file likely already had them).
  5. sudo systemctl start vast-manager — The service is started with the new binary.
  6. sleep 1 — A one-second pause gives the service time to initialize, bind its HTTP port, and open its SQLite database.
  7. sudo systemctl is-active vast-manager — The final verification step. This command exits with status 0 and prints "active" if the service is running, or prints "inactive" / "failed" and exits non-zero if something went wrong. The entire chain is connected with && operators, meaning any failure aborts the sequence. This is a deliberate choice: if the SCP fails, we don't stop a running service for no reason. If the stop fails, we don't attempt to replace the binary. If the start fails, we don't get a false positive from the verification. The && chaining transforms a sequence of operations into a transactional deployment unit.

Assumptions and Risks

The deployment makes several assumptions. It assumes SSH access to 10.1.2.104 with passwordless sudo, which has been established earlier in the session. It assumes the vast-manager systemd unit file exists and is correctly configured. It assumes the binary, compiled on a different machine with GOOS=linux GOARCH=amd64, is compatible with the controller's Linux environment — a reasonable assumption given the Go cross-compilation toolchain, but one that could fail if the controller had unusual library dependencies or a different libc.

A subtle risk is that the LSP diagnostics from earlier edits reported ERROR [31:12] pattern ui.html: no matching files found. This error comes from the embedded file pattern in the Go source (//go:embed ui.html), which tells the Go compiler to embed the ui.html file into the binary at compile time. If the LSP couldn't find the file, it might indicate the build was run from the wrong working directory. However, the Go compiler itself did not report this as an error — the build succeeded — suggesting the LSP diagnostic was a false positive or the file was found at compile time despite the editor's confusion. The deployment implicitly trusts the build output.

Another assumption is that no other artifacts need updating. The ui.html template is embedded in the binary, so a single binary deployment suffices. But if there were configuration files, environment variables, or database migrations that needed manual intervention, this command would not cover them. The database migration (adding columns via ALTER TABLE) runs automatically when the new binary starts and calls NewServer(), so that is handled.

The Bigger Picture

Message 1401 is a reminder that in distributed systems, operational visibility is a first-class engineering concern. The ability to see what happened to an instance after it was destroyed is not a luxury — it is essential for debugging, capacity planning, and cost optimization. The assistant's work in the preceding messages transformed the vast-manager from a system that could only show the present into one that preserves the past. This deployment made that transformation live.

The "active" response is the system's confirmation that the new logic is in place. From this moment forward, every instance that passes through the manager will have its metadata permanently recorded. When an instance is killed, its GPU model, location, cost, and benchmark results will remain visible in the dashboard for seven days. The data-driven hardware discovery system will have the historical context it needs to make informed recommendations. The loop is closed.

In the broader narrative of the coding session, this message represents a transition from feature development to operational hardening. The assistant had built the offers panel, the deployment workflow, the performance tracking system, and the ignore/unignore functionality. But all of those features were built on a fragile foundation: data that evaporated when instances died. Message 1401 is the moment that foundation was reinforced, ensuring that the system could learn from its own history rather than forget it.